Efficient random saliency map detection

Most image retargeting algorithms rely heavily on valid saliency map detection to proceed. However, the inefficiency of high quality saliency map detection severely restricts the application of these image retargeting methods. In this paper,we propose a random algorithm for efficient context-aware s...

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Bibliographic Details
Published in:Science China. Information sciences 2011-06, Vol.54 (6), p.1207-1217
Main Authors: Huang, ZhiYong, He, FaZhi, Cai, XianTao, Zou, ZhengQin, Liu, Jing, Liang, MingMing, Chen, Xiao
Format: Article
Language:English
Subjects:
Algorithms
China
Computer Science
Construction
Data structures
Image processing
Information Systems and Communication Service
Research Papers
Salience
Searching
State of the art
图像处理
地图
定位方法
定位算法
检测结果
算法集成
随机搜索
随机算法
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Description
Summary:Most image retargeting algorithms rely heavily on valid saliency map detection to proceed. However, the inefficiency of high quality saliency map detection severely restricts the application of these image retargeting methods. In this paper,we propose a random algorithm for efficient context-aware saliency map detection. Our method is a multiple level saliency map detection algorithm that integrates multiple level coarse saliency maps into the resulting saliency map and selectively updates unreliable regions of the saliency map to refine detection results. Because of the randomized search, our method requires very little additional memory beyond that for the input image and result map, and does not need to build auxiliary data structures to accelerate the saliency map detection. We have implemented our algorithm on a GPU and demonstrated the performance for a variety of images and video sequences, compared with state-of-the-art image processing.
ISSN:1674-733X
1869-1919
DOI:10.1007/s11432-011-4263-2